Triple
T33341172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ntoum |
E853670
|
entity |
| Predicate | railDirectionFromLibreville |
P176519
|
FINISHED |
| Object | inland |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: inland | Statement: [Ntoum, railDirectionFromLibreville, inland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railDirectionFromLibreville Context triple: [Ntoum, railDirectionFromLibreville, inland]
-
A.
distanceFromBangui_km
Indicates the distance, measured in kilometers, between a given location and Bangui.
-
B.
distanceFromOuagadougou_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Ouagadougou.
-
C.
distanceFromCotonou
Indicates the measured spatial distance between a given location and the city of Cotonou.
-
D.
distanceFromDakar
Indicates the spatial distance between a given entity’s location and the city of Dakar.
-
E.
directionFromDarEsSalaam
Indicates the cardinal or relative compass direction in which one entity is located from Dar es Salaam.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6e312d7fc819094dec41810f2585d |
completed | May 3, 2026, 5:54 a.m. |
Created at: May 1, 2026, 1:34 a.m.